Part four: what data should you collect?by
By Jennifer Kirkby, consulting editor
So, on the basis you shouldn't collect everything, what data might be useful?
Master data – key, must-have data to fulfil the basic relationship. It must be accurate and completely up to date.
• Name, addresses, telephone, e-mail and website (also includes role if in B2B).
• Preferences for contact, privacy and passwords.
• Product holding and services.
• Key events, eg renewal dates, contract dates.
• Credit rating and trustworthiness.
• Unique reference code.
Descriptive – data used to profile the customer, often for segmentation and prediction. The challenge is to keep it relevant and up to date. It can include actual or modelled data, eg segment membership.
• B2C - date of birth, sex, lifestage, lifestyle, attitudinal.
• B2B - industry, revenue, size, contacts (and their personal information ), market share and ranking, CRM maturity.
Behavioural – data used for analysis (eg "cost to serve") and prediction to manage the relationship. The challenge is to keep it up to date, transform it to a relevant level for use and integrate it. Many companies have still not integrated website data.
• Transaction - product use, click stream, spend, channels used.
• Contacts and response - enquiries, response to campaigns, position in sales pipeline, inclusion in research, times log onto internet.
• Usage - in what circumstances does the customer use your product, eg "direct seller", "shops on a Monday", "takes regular foreign holidays".
Relationship – data used to gauge the degree of relationship and how to engage further. B2B companies may keep this on individuals in an organization. This is data kept at a personal level and does not need such a high degree of completeness for every customer, except if it is to be used for research.
• Feedback and complaints including emotional and attitudinal data.
• Events – birthday, invitations, lifestage changes.
• Peferences, goals and requirements for tailoring the proposition.
• Net promoter score, known recommendations.
• Modelled – profitability value, loyalty, relationship stage, propensity to churn.
• Next best action.
• Co-creating willingness to take part in research, trials, member of a user group or online community.
Contextual – data that enhances the understanding of the relationship, degree of influence and market positioning. This is often used for personal relationship building.
• Competitors for the customer.
• A client’s competitors.
• Degree of market influence by the individual or company.
• Bogging activity.
• Awards won.
• Content from the news on the industry or client.
• Key word tags from stories.
Part five, creating actionable insight from data, click here.